import recommendations

recommendations.sim_distance(recommendations.critics, 'Lisa Rose', 'Gene Seymour');

recommendations.sim_pearson(recommendations.critics, 'Lisa Rose', 'Gene Seymour');

recommendations.topMatches(recommendations.critics, 'Toby', n=3)

recommendations.getRecommendations(recommendations.critics, 'Toby')

movies = recommendations.transformPrefs(recommendations.critics)

movies

recommendations.topMatches(movies, 'Superman Returns', n=3)

import pydelicious

pydelicious.get_popular(tag="programming")

